Overview

Dataset statistics

Number of variables57
Number of observations693071
Missing cells55095
Missing cells (%)0.1%
Total size in memory301.4 MiB
Average record size in memory456.0 B

Variable types

Text11
Numeric46

Alerts

timezone has constant value ""Constant
price has 55095 (7.9%) missing valuesMissing
id has unique valuesUnique
hour has 32413 (4.7%) zerosZeros
precipIntensity has 542243 (78.2%) zerosZeros
precipProbability has 542243 (78.2%) zerosZeros
cloudCover has 39547 (5.7%) zerosZeros
uvIndex has 533664 (77.0%) zerosZeros
precipIntensityMax has 228096 (32.9%) zerosZeros

Reproduction

Analysis started2023-06-03 16:29:40.940938
Analysis finished2023-06-03 16:29:51.388134
Duration10.45 seconds
Software versionydata-profiling vv4.2.0
Download configurationconfig.json

Variables

id
Text

Distinct693071
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.3 MiB
2023-06-03T22:29:52.180880image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length36
Median length36
Mean length36
Min length36

Characters and Unicode

Total characters24950556
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique693071 ?
Unique (%)100.0%

Sample

1st row424553bb-7174-41ea-aeb4-fe06d4f4b9d7
2nd row4bd23055-6827-41c6-b23b-3c491f24e74d
3rd row981a3613-77af-4620-a42a-0c0866077d1e
4th rowc2d88af2-d278-4bfd-a8d0-29ca77cc5512
5th rowe0126e1f-8ca9-4f2e-82b3-50505a09db9a
ValueCountFrequency (%)
424553bb-7174-41ea-aeb4-fe06d4f4b9d7 1
 
< 0.1%
4f9fee41-fde3-4767-bbf1-a00e108701fb 1
 
< 0.1%
c05d4e09-3f00-43cf-a0d8-6f38c0f4d04a 1
 
< 0.1%
18d580ac-c91a-4b6d-aa75-ab62566f713e 1
 
< 0.1%
981a3613-77af-4620-a42a-0c0866077d1e 1
 
< 0.1%
c2d88af2-d278-4bfd-a8d0-29ca77cc5512 1
 
< 0.1%
e0126e1f-8ca9-4f2e-82b3-50505a09db9a 1
 
< 0.1%
f6f6d7e4-3e18-4922-a5f5-181cdd3fa6f2 1
 
< 0.1%
462816a3-820d-408b-8549-0b39e82f65ac 1
 
< 0.1%
474d6376-bc59-4ec9-bf57-4e6d6faeb165 1
 
< 0.1%
Other values (693061) 693061
> 99.9%
2023-06-03T22:29:53.077079image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 2772284
 
11.1%
4 1991182
 
8.0%
b 1473736
 
5.9%
a 1473624
 
5.9%
9 1472641
 
5.9%
8 1472196
 
5.9%
f 1301393
 
5.2%
6 1301283
 
5.2%
d 1300911
 
5.2%
7 1300859
 
5.2%
Other values (7) 9090447
36.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14032223
56.2%
Lowercase Letter 8146049
32.6%
Dash Punctuation 2772284
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 1991182
14.2%
9 1472641
10.5%
8 1472196
10.5%
6 1301283
9.3%
7 1300859
9.3%
1 1300029
9.3%
3 1299078
9.3%
0 1299061
9.3%
5 1298412
9.3%
2 1297482
9.2%
Lowercase Letter
ValueCountFrequency (%)
b 1473736
18.1%
a 1473624
18.1%
f 1301393
16.0%
d 1300911
16.0%
c 1298471
15.9%
e 1297914
15.9%
Dash Punctuation
ValueCountFrequency (%)
- 2772284
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 16804507
67.4%
Latin 8146049
32.6%

Most frequent character per script

Common
ValueCountFrequency (%)
- 2772284
16.5%
4 1991182
11.8%
9 1472641
8.8%
8 1472196
8.8%
6 1301283
7.7%
7 1300859
7.7%
1 1300029
7.7%
3 1299078
7.7%
0 1299061
7.7%
5 1298412
7.7%
Latin
ValueCountFrequency (%)
b 1473736
18.1%
a 1473624
18.1%
f 1301393
16.0%
d 1300911
16.0%
c 1298471
15.9%
e 1297914
15.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24950556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 2772284
 
11.1%
4 1991182
 
8.0%
b 1473736
 
5.9%
a 1473624
 
5.9%
9 1472641
 
5.9%
8 1472196
 
5.9%
f 1301393
 
5.2%
6 1301283
 
5.2%
d 1300911
 
5.2%
7 1300859
 
5.2%
Other values (7) 9090447
36.4%

timestamp
Real number (ℝ)

Distinct36179
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1544045710
Minimum1543203646
Maximum1545160511
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:29:53.214123image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1543203646
5-th percentile1543279525
Q11543443968
median1543737478
Q31544827509
95-th percentile1545093912
Maximum1545160511
Range1956865
Interquartile range (IQR)1383541

Descriptive statistics

Standard deviation689192.4926
Coefficient of variation (CV)0.0004463549804
Kurtosis-1.563675635
Mean1544045710
Median Absolute Deviation (MAD)397476
Skewness0.4325804981
Sum1.070133304 × 1015
Variance4.749862918 × 1011
MonotonicityNot monotonic
2023-06-03T22:29:53.328693image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1545000000 461
 
0.1%
1543431008 156
 
< 0.1%
1543441988 156
 
< 0.1%
1543414808 156
 
< 0.1%
1543412468 156
 
< 0.1%
1543463048 156
 
< 0.1%
1543418048 156
 
< 0.1%
1543422188 156
 
< 0.1%
1543402568 156
 
< 0.1%
1543401488 156
 
< 0.1%
Other values (36169) 691206
99.7%
ValueCountFrequency (%)
1543203646 21
< 0.1%
1543203647 42
< 0.1%
1543203648 21
< 0.1%
1543207255 7
 
< 0.1%
1543207256 35
< 0.1%
ValueCountFrequency (%)
1545160511 32
< 0.1%
1545160510 13
 
< 0.1%
1545160509 50
< 0.1%
1545160507 11
 
< 0.1%
1545160507 1
 
< 0.1%

hour
Real number (ℝ)

Distinct24
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.61913714
Minimum0
Maximum23
Zeros32413
Zeros (%)4.7%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:29:53.440265image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q16
median12
Q318
95-th percentile22
Maximum23
Range23
Interquartile range (IQR)12

Descriptive statistics

Standard deviation6.948114156
Coefficient of variation (CV)0.5979888239
Kurtosis-1.18122704
Mean11.61913714
Median Absolute Deviation (MAD)6
Skewness-0.04543235624
Sum8052887
Variance48.27629033
MonotonicityNot monotonic
2023-06-03T22:29:53.531831image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 32413
 
4.7%
23 31931
 
4.6%
16 30384
 
4.4%
17 30384
 
4.4%
12 30384
 
4.4%
13 30384
 
4.4%
18 30384
 
4.4%
11 30384
 
4.4%
14 30384
 
4.4%
10 30384
 
4.4%
Other values (14) 385655
55.6%
ValueCountFrequency (%)
0 32413
4.7%
1 28548
4.1%
2 28548
4.1%
3 27815
4.0%
4 28330
4.1%
ValueCountFrequency (%)
23 31931
4.6%
22 29436
4.2%
21 27732
4.0%
20 26782
3.9%
19 27555
4.0%

day
Real number (ℝ)

Distinct17
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.7943645
Minimum1
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:29:53.621388image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q113
median17
Q328
95-th percentile30
Maximum30
Range29
Interquartile range (IQR)15

Descriptive statistics

Standard deviation9.982286014
Coefficient of variation (CV)0.5609801919
Kurtosis-1.184557885
Mean17.7943645
Median Absolute Deviation (MAD)10
Skewness-0.3754714064
Sum12332758
Variance99.64603406
MonotonicityNot monotonic
2023-06-03T22:29:53.708387image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
27 76121
11.0%
28 73691
10.6%
29 59974
 
8.7%
1 45240
 
6.5%
30 45084
 
6.5%
16 44928
 
6.5%
15 44928
 
6.5%
14 44928
 
6.5%
3 44928
 
6.5%
2 44928
 
6.5%
Other values (7) 168321
24.3%
ValueCountFrequency (%)
1 45240
6.5%
2 44928
6.5%
3 44928
6.5%
4 12636
 
1.8%
9 1674
 
0.2%
ValueCountFrequency (%)
30 45084
6.5%
29 59974
8.7%
28 73691
10.6%
27 76121
11.0%
26 31587
4.6%

month
Real number (ℝ)

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.58668448
Minimum11
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:29:53.799918image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile11
Q111
median12
Q312
95-th percentile12
Maximum12
Range1
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.492428828
Coefficient of variation (CV)0.04249954582
Kurtosis-1.876052064
Mean11.58668448
Median Absolute Deviation (MAD)0
Skewness-0.3520700914
Sum8030395
Variance0.2424861506
MonotonicityNot monotonic
2023-06-03T22:29:53.874442image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
12 406614
58.7%
11 286457
41.3%
ValueCountFrequency (%)
11 286457
41.3%
12 406614
58.7%
ValueCountFrequency (%)
12 406614
58.7%
11 286457
41.3%
Distinct31350
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size5.3 MiB
2023-06-03T22:29:53.984982image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters13168349
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row2018-12-16 09:30:07
2nd row2018-11-27 02:00:23
3rd row2018-11-28 01:00:22
4th row2018-11-30 04:53:02
5th row2018-11-29 03:49:20
ValueCountFrequency (%)
2018-11-27 76121
 
5.5%
2018-11-28 73691
 
5.3%
2018-11-29 59974
 
4.3%
2018-12-01 45240
 
3.3%
2018-11-30 45084
 
3.3%
2018-12-15 44928
 
3.2%
2018-12-17 44928
 
3.2%
2018-12-02 44928
 
3.2%
2018-12-03 44928
 
3.2%
2018-12-16 44928
 
3.2%
Other values (11517) 861392
62.1%
2023-06-03T22:29:54.210050image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2712152
20.6%
2 1963141
14.9%
0 1940265
14.7%
- 1386142
10.5%
: 1386142
10.5%
8 1029159
 
7.8%
693071
 
5.3%
3 529317
 
4.0%
5 493170
 
3.7%
4 312486
 
2.4%
Other values (3) 723304
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9702994
73.7%
Dash Punctuation 1386142
 
10.5%
Other Punctuation 1386142
 
10.5%
Space Separator 693071
 
5.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2712152
28.0%
2 1963141
20.2%
0 1940265
20.0%
8 1029159
 
10.6%
3 529317
 
5.5%
5 493170
 
5.1%
4 312486
 
3.2%
7 306507
 
3.2%
6 211458
 
2.2%
9 205339
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
- 1386142
100.0%
Other Punctuation
ValueCountFrequency (%)
: 1386142
100.0%
Space Separator
ValueCountFrequency (%)
693071
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13168349
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2712152
20.6%
2 1963141
14.9%
0 1940265
14.7%
- 1386142
10.5%
: 1386142
10.5%
8 1029159
 
7.8%
693071
 
5.3%
3 529317
 
4.0%
5 493170
 
3.7%
4 312486
 
2.4%
Other values (3) 723304
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13168349
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2712152
20.6%
2 1963141
14.9%
0 1940265
14.7%
- 1386142
10.5%
: 1386142
10.5%
8 1029159
 
7.8%
693071
 
5.3%
3 529317
 
4.0%
5 493170
 
3.7%
4 312486
 
2.4%
Other values (3) 723304
 
5.5%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.3 MiB
2023-06-03T22:29:54.414114image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length16
Median length16
Mean length16
Min length16

Characters and Unicode

Total characters11089136
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAmerica/New_York
2nd rowAmerica/New_York
3rd rowAmerica/New_York
4th rowAmerica/New_York
5th rowAmerica/New_York
ValueCountFrequency (%)
america/new_york 693071
100.0%
2023-06-03T22:29:54.695070image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1386142
12.5%
r 1386142
12.5%
A 693071
 
6.2%
m 693071
 
6.2%
i 693071
 
6.2%
c 693071
 
6.2%
a 693071
 
6.2%
/ 693071
 
6.2%
N 693071
 
6.2%
w 693071
 
6.2%
Other values (4) 2772284
25.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 7623781
68.8%
Uppercase Letter 2079213
 
18.8%
Other Punctuation 693071
 
6.2%
Connector Punctuation 693071
 
6.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1386142
18.2%
r 1386142
18.2%
m 693071
9.1%
i 693071
9.1%
c 693071
9.1%
a 693071
9.1%
w 693071
9.1%
o 693071
9.1%
k 693071
9.1%
Uppercase Letter
ValueCountFrequency (%)
A 693071
33.3%
N 693071
33.3%
Y 693071
33.3%
Other Punctuation
ValueCountFrequency (%)
/ 693071
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 693071
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9702994
87.5%
Common 1386142
 
12.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1386142
14.3%
r 1386142
14.3%
A 693071
7.1%
m 693071
7.1%
i 693071
7.1%
c 693071
7.1%
a 693071
7.1%
N 693071
7.1%
w 693071
7.1%
Y 693071
7.1%
Other values (2) 1386142
14.3%
Common
ValueCountFrequency (%)
/ 693071
50.0%
_ 693071
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11089136
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 1386142
12.5%
r 1386142
12.5%
A 693071
 
6.2%
m 693071
 
6.2%
i 693071
 
6.2%
c 693071
 
6.2%
a 693071
 
6.2%
/ 693071
 
6.2%
N 693071
 
6.2%
w 693071
 
6.2%
Other values (4) 2772284
25.0%

source
Text

Distinct12
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.3 MiB
2023-06-03T22:29:54.830116image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length23
Median length16
Mean length13.17692415
Min length6

Characters and Unicode

Total characters9132544
Distinct characters30
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowHaymarket Square
2nd rowHaymarket Square
3rd rowHaymarket Square
4th rowHaymarket Square
5th rowHaymarket Square
ValueCountFrequency (%)
district 116670
 
8.8%
university 115520
 
8.7%
end 115325
 
8.7%
north 114881
 
8.6%
station 114868
 
8.6%
financial 58857
 
4.4%
theatre 57813
 
4.4%
back 57792
 
4.4%
bay 57792
 
4.4%
boston 57764
 
4.3%
Other values (8) 461103
34.7%
2023-06-03T22:29:55.074990image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 1097614
12.0%
i 754365
 
8.3%
a 752103
 
8.2%
n 694107
 
7.6%
r 635868
 
7.0%
635314
 
7.0%
e 634852
 
7.0%
o 518186
 
5.7%
s 405272
 
4.4%
c 290722
 
3.2%
Other values (20) 2714141
29.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 7168845
78.5%
Uppercase Letter 1328385
 
14.5%
Space Separator 635314
 
7.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 1097614
15.3%
i 754365
10.5%
a 752103
10.5%
n 694107
9.7%
r 635868
8.9%
e 634852
8.9%
o 518186
7.2%
s 405272
 
5.7%
c 290722
 
4.1%
y 288805
 
4.0%
Other values (9) 1096951
15.3%
Uppercase Letter
ValueCountFrequency (%)
B 230751
17.4%
S 230354
17.3%
N 172637
13.0%
D 116670
8.8%
F 116614
8.8%
U 115520
8.7%
E 115325
8.7%
H 115139
8.7%
T 57813
 
4.4%
W 57562
 
4.3%
Space Separator
ValueCountFrequency (%)
635314
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8497230
93.0%
Common 635314
 
7.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 1097614
12.9%
i 754365
 
8.9%
a 752103
 
8.9%
n 694107
 
8.2%
r 635868
 
7.5%
e 634852
 
7.5%
o 518186
 
6.1%
s 405272
 
4.8%
c 290722
 
3.4%
y 288805
 
3.4%
Other values (19) 2425336
28.5%
Common
ValueCountFrequency (%)
635314
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9132544
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 1097614
12.0%
i 754365
 
8.3%
a 752103
 
8.2%
n 694107
 
7.6%
r 635868
 
7.0%
635314
 
7.0%
e 634852
 
7.0%
o 518186
 
5.7%
s 405272
 
4.4%
c 290722
 
3.2%
Other values (20) 2714141
29.7%
Distinct12
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.3 MiB
2023-06-03T22:29:55.205567image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length23
Median length16
Mean length13.1769559
Min length6

Characters and Unicode

Total characters9132566
Distinct characters30
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNorth Station
2nd rowNorth Station
3rd rowNorth Station
4th rowNorth Station
5th rowNorth Station
ValueCountFrequency (%)
district 116649
 
8.8%
university 115519
 
8.7%
end 115331
 
8.7%
north 114875
 
8.6%
station 114868
 
8.6%
financial 58851
 
4.4%
theatre 57798
 
4.4%
back 57780
 
4.3%
bay 57780
 
4.3%
haymarket 57764
 
4.3%
Other values (8) 461170
34.7%
2023-06-03T22:29:55.450171image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 1097588
12.0%
i 754309
 
8.3%
a 752135
 
8.2%
n 694099
 
7.6%
r 635879
 
7.0%
635314
 
7.0%
e 634888
 
7.0%
o 518178
 
5.7%
s 405262
 
4.4%
c 290683
 
3.2%
Other values (20) 2714231
29.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 7168867
78.5%
Uppercase Letter 1328385
 
14.5%
Space Separator 635314
 
7.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 1097588
15.3%
i 754309
10.5%
a 752135
10.5%
n 694099
9.7%
r 635879
8.9%
e 634888
8.9%
o 518178
7.2%
s 405262
 
5.7%
c 290683
 
4.1%
y 288820
 
4.0%
Other values (9) 1097026
15.3%
Uppercase Letter
ValueCountFrequency (%)
B 230727
17.4%
S 230381
17.3%
N 172630
13.0%
D 116649
8.8%
F 116608
8.8%
U 115519
8.7%
E 115331
8.7%
H 115167
8.7%
T 57798
 
4.4%
W 57575
 
4.3%
Space Separator
ValueCountFrequency (%)
635314
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8497252
93.0%
Common 635314
 
7.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 1097588
12.9%
i 754309
 
8.9%
a 752135
 
8.9%
n 694099
 
8.2%
r 635879
 
7.5%
e 634888
 
7.5%
o 518178
 
6.1%
s 405262
 
4.8%
c 290683
 
3.4%
y 288820
 
3.4%
Other values (19) 2425411
28.5%
Common
ValueCountFrequency (%)
635314
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9132566
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 1097588
12.0%
i 754309
 
8.3%
a 752135
 
8.2%
n 694099
 
7.6%
r 635879
 
7.0%
635314
 
7.0%
e 634888
 
7.0%
o 518178
 
5.7%
s 405262
 
4.4%
c 290683
 
3.2%
Other values (20) 2714231
29.7%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.3 MiB
2023-06-03T22:29:55.555673image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters2772284
Distinct characters8
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowLyft
2nd rowLyft
3rd rowLyft
4th rowLyft
5th rowLyft
ValueCountFrequency (%)
uber 385663
55.6%
lyft 307408
44.4%
2023-06-03T22:29:55.754709image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
U 385663
13.9%
b 385663
13.9%
e 385663
13.9%
r 385663
13.9%
L 307408
11.1%
y 307408
11.1%
f 307408
11.1%
t 307408
11.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2079213
75.0%
Uppercase Letter 693071
 
25.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
b 385663
18.5%
e 385663
18.5%
r 385663
18.5%
y 307408
14.8%
f 307408
14.8%
t 307408
14.8%
Uppercase Letter
ValueCountFrequency (%)
U 385663
55.6%
L 307408
44.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 2772284
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U 385663
13.9%
b 385663
13.9%
e 385663
13.9%
r 385663
13.9%
L 307408
11.1%
y 307408
11.1%
f 307408
11.1%
t 307408
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2772284
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U 385663
13.9%
b 385663
13.9%
e 385663
13.9%
r 385663
13.9%
L 307408
11.1%
y 307408
11.1%
f 307408
11.1%
t 307408
11.1%
Distinct13
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.3 MiB
2023-06-03T22:29:55.895217image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length36
Median length36
Mean length23.95036728
Min length4

Characters and Unicode

Total characters16599305
Distinct characters30
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowlyft_line
2nd rowlyft_premier
3rd rowlyft
4th rowlyft_luxsuv
5th rowlyft_plus
ValueCountFrequency (%)
6f72dfc5-27f1-42e8-84db-ccc7a75f6969 55096
 
7.9%
9a0e7b09-b92b-4c41-9779-2ad22b4d779d 55096
 
7.9%
6d318bcc-22a3-4af6-bddd-b409bfce1546 55096
 
7.9%
6c84fd89-3f11-4782-9b50-97c468b19529 55095
 
7.9%
8cf7e821-f0d3-49c6-8eba-e679c0ebcf6a 55095
 
7.9%
55c66225-fbe7-4fd5-9072-eab1ece5e23e 55094
 
7.9%
997acbb5-e102-41e1-b155-9df7de0a73f2 55091
 
7.9%
lyft_premier 51235
 
7.4%
lyft 51235
 
7.4%
lyft_luxsuv 51235
 
7.4%
Other values (3) 153703
22.2%
2023-06-03T22:29:56.149817image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1542652
 
9.3%
f 1133829
 
6.8%
9 1101896
 
6.6%
e 1035208
 
6.2%
2 991707
 
6.0%
7 991705
 
6.0%
b 991705
 
6.0%
c 936617
 
5.6%
4 771333
 
4.6%
d 771330
 
4.6%
Other values (20) 6331323
38.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 7417788
44.7%
Decimal Number 7382692
44.5%
Dash Punctuation 1542652
 
9.3%
Connector Punctuation 256173
 
1.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
f 1133829
15.3%
e 1035208
14.0%
b 991705
13.4%
c 936617
12.6%
d 771330
10.4%
a 550946
7.4%
l 512346
6.9%
y 307408
 
4.1%
t 307408
 
4.1%
u 204940
 
2.8%
Other values (8) 666051
9.0%
Decimal Number
ValueCountFrequency (%)
9 1101896
14.9%
2 991707
13.4%
7 991705
13.4%
4 771333
10.4%
6 716239
9.7%
1 716222
9.7%
5 716221
9.7%
8 550953
7.5%
0 495849
6.7%
3 330567
 
4.5%
Dash Punctuation
ValueCountFrequency (%)
- 1542652
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 256173
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9181517
55.3%
Latin 7417788
44.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
f 1133829
15.3%
e 1035208
14.0%
b 991705
13.4%
c 936617
12.6%
d 771330
10.4%
a 550946
7.4%
l 512346
6.9%
y 307408
 
4.1%
t 307408
 
4.1%
u 204940
 
2.8%
Other values (8) 666051
9.0%
Common
ValueCountFrequency (%)
- 1542652
16.8%
9 1101896
12.0%
2 991707
10.8%
7 991705
10.8%
4 771333
8.4%
6 716239
7.8%
1 716222
7.8%
5 716221
7.8%
8 550953
 
6.0%
0 495849
 
5.4%
Other values (2) 586740
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16599305
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1542652
 
9.3%
f 1133829
 
6.8%
9 1101896
 
6.6%
e 1035208
 
6.2%
2 991707
 
6.0%
7 991705
 
6.0%
b 991705
 
6.0%
c 936617
 
5.6%
4 771333
 
4.6%
d 771330
 
4.6%
Other values (20) 6331323
38.1%

name
Text

Distinct13
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.3 MiB
2023-06-03T22:29:56.270345image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length12
Median length7
Mean length6.210624885
Min length3

Characters and Unicode

Total characters4304404
Distinct characters27
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowShared
2nd rowLux
3rd rowLyft
4th rowLux Black XL
5th rowLyft XL
ValueCountFrequency (%)
black 212661
22.3%
lux 153705
16.1%
lyft 102470
10.8%
xl 102470
10.8%
uberxl 55096
 
5.8%
wav 55096
 
5.8%
suv 55096
 
5.8%
taxi 55095
 
5.8%
uberx 55094
 
5.8%
uberpool 55091
 
5.8%
2023-06-03T22:29:56.473082image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
L 413741
 
9.6%
a 318989
 
7.4%
l 267752
 
6.2%
260036
 
6.0%
U 220377
 
5.1%
e 216514
 
5.0%
r 216514
 
5.0%
B 212661
 
4.9%
c 212661
 
4.9%
k 212661
 
4.9%
Other values (17) 1752498
40.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2548030
59.2%
Uppercase Letter 1496338
34.8%
Space Separator 260036
 
6.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 318989
12.5%
l 267752
10.5%
e 216514
8.5%
r 216514
8.5%
c 212661
8.3%
k 212661
8.3%
x 208800
8.2%
b 165281
 
6.5%
u 153705
 
6.0%
o 110182
 
4.3%
Other values (6) 464971
18.2%
Uppercase Letter
ValueCountFrequency (%)
L 413741
27.7%
U 220377
14.7%
B 212661
14.2%
X 212660
14.2%
V 110192
 
7.4%
S 106329
 
7.1%
W 55096
 
3.7%
A 55096
 
3.7%
T 55095
 
3.7%
P 55091
 
3.7%
Space Separator
ValueCountFrequency (%)
260036
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4044368
94.0%
Common 260036
 
6.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
L 413741
 
10.2%
a 318989
 
7.9%
l 267752
 
6.6%
U 220377
 
5.4%
e 216514
 
5.4%
r 216514
 
5.4%
B 212661
 
5.3%
c 212661
 
5.3%
k 212661
 
5.3%
X 212660
 
5.3%
Other values (16) 1539838
38.1%
Common
ValueCountFrequency (%)
260036
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4304404
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
L 413741
 
9.6%
a 318989
 
7.4%
l 267752
 
6.2%
260036
 
6.0%
U 220377
 
5.1%
e 216514
 
5.0%
r 216514
 
5.0%
B 212661
 
4.9%
c 212661
 
4.9%
k 212661
 
4.9%
Other values (17) 1752498
40.7%

price
Real number (ℝ)

Distinct147
Distinct (%)< 0.1%
Missing55095
Missing (%)7.9%
Infinite0
Infinite (%)0.0%
Mean16.54512549
Minimum2.5
Maximum97.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:29:56.599623image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum2.5
5-th percentile6.5
Q19
median13.5
Q322.5
95-th percentile34
Maximum97.5
Range95
Interquartile range (IQR)13.5

Descriptive statistics

Standard deviation9.324358581
Coefficient of variation (CV)0.5635713423
Kurtosis1.224829254
Mean16.54512549
Median Absolute Deviation (MAD)6
Skewness1.045747056
Sum10555392.98
Variance86.94366295
MonotonicityNot monotonic
2023-06-03T22:29:56.714319image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7 52314
 
7.5%
16.5 44351
 
6.4%
10.5 40590
 
5.9%
13.5 33707
 
4.9%
9 30884
 
4.5%
27.5 28221
 
4.1%
19.5 26591
 
3.8%
22.5 26568
 
3.8%
26 26226
 
3.8%
9.5 22738
 
3.3%
Other values (137) 305786
44.1%
(Missing) 55095
 
7.9%
ValueCountFrequency (%)
2.5 211
 
< 0.1%
3 5543
 
0.8%
3.5 5063
 
0.7%
4.5 419
 
0.1%
5 14084
2.0%
ValueCountFrequency (%)
97.5 1
 
< 0.1%
92 9
< 0.1%
89.5 1
 
< 0.1%
89 11
< 0.1%
87.5 4
 
< 0.1%

distance
Real number (ℝ)

Distinct549
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.189429755
Minimum0.02
Maximum7.86
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:29:56.825844image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.02
5-th percentile0.58
Q11.28
median2.16
Q32.92
95-th percentile4.46
Maximum7.86
Range7.84
Interquartile range (IQR)1.64

Descriptive statistics

Standard deviation1.138936987
Coefficient of variation (CV)0.5201980032
Kurtosis1.228017651
Mean2.189429755
Median Absolute Deviation (MAD)0.82
Skewness0.8343950078
Sum1517430.27
Variance1.29717746
MonotonicityNot monotonic
2023-06-03T22:29:56.938358image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.66 9174
 
1.3%
2.32 9127
 
1.3%
2.84 8562
 
1.2%
1.41 7884
 
1.1%
1.25 7434
 
1.1%
1.16 7333
 
1.1%
1.08 7251
 
1.0%
1.34 7105
 
1.0%
1.5 7067
 
1.0%
1.35 6952
 
1.0%
Other values (539) 615182
88.8%
ValueCountFrequency (%)
0.02 70
 
< 0.1%
0.03 238
< 0.1%
0.04 98
< 0.1%
0.12 63
 
< 0.1%
0.17 35
 
< 0.1%
ValueCountFrequency (%)
7.86 7
 
< 0.1%
7.62 7
 
< 0.1%
7.5 21
 
< 0.1%
7.46 1575
0.2%
7.45 7
 
< 0.1%

surge_multiplier
Real number (ℝ)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.013869791
Minimum1
Maximum3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:29:57.037859image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum3
Range2
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.0916412621
Coefficient of variation (CV)0.0903876049
Kurtosis80.5346047
Mean1.013869791
Median Absolute Deviation (MAD)0
Skewness8.320248047
Sum702683.75
Variance0.008398120919
MonotonicityNot monotonic
2023-06-03T22:29:57.121375image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 672096
97.0%
1.25 11085
 
1.6%
1.5 5065
 
0.7%
1.75 2420
 
0.3%
2 2239
 
0.3%
2.5 154
 
< 0.1%
3 12
 
< 0.1%
ValueCountFrequency (%)
1 672096
97.0%
1.25 11085
 
1.6%
1.5 5065
 
0.7%
1.75 2420
 
0.3%
2 2239
 
0.3%
ValueCountFrequency (%)
3 12
 
< 0.1%
2.5 154
 
< 0.1%
2 2239
0.3%
1.75 2420
0.3%
1.5 5065
0.7%

latitude
Real number (ℝ)

Distinct11
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42.33817248
Minimum42.2148
Maximum42.3661
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:29:57.218898image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum42.2148
5-th percentile42.2148
Q142.3503
median42.3519
Q342.3647
95-th percentile42.3661
Maximum42.3661
Range0.1513
Interquartile range (IQR)0.0144

Descriptive statistics

Standard deviation0.04783976568
Coefficient of variation (CV)0.00112994404
Kurtosis2.690387661
Mean42.33817248
Median Absolute Deviation (MAD)0.0121
Skewness-2.116051626
Sum29343359.54
Variance0.00228864318
MonotonicityNot monotonic
2023-06-03T22:29:57.303933image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
42.3519 112082
16.2%
42.3647 98690
14.2%
42.3661 95146
13.7%
42.2148 88546
12.8%
42.3503 61216
8.8%
42.3505 54713
7.9%
42.3644 42456
 
6.1%
42.3429 42218
 
6.1%
42.3588 42048
 
6.1%
42.3398 29748
 
4.3%
ValueCountFrequency (%)
42.2148 88546
12.8%
42.3398 29748
 
4.3%
42.3429 42218
6.1%
42.3503 61216
8.8%
42.3505 54713
7.9%
ValueCountFrequency (%)
42.3661 95146
13.7%
42.3647 98690
14.2%
42.3644 42456
6.1%
42.3588 42048
6.1%
42.3559 26208
 
3.8%

longitude
Real number (ℝ)

Distinct12
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-71.06615082
Minimum-71.1054
Maximum-71.033
Zeros0
Zeros (%)0.0%
Negative693071
Negative (%)100.0%
Memory size5.3 MiB
2023-06-03T22:29:57.399274image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-71.1054
5-th percentile-71.1054
Q1-71.081
median-71.0631
Q3-71.0542
95-th percentile-71.033
Maximum-71.033
Range0.0724
Interquartile range (IQR)0.0268

Descriptive statistics

Standard deviation0.02030204379
Coefficient of variation (CV)-0.000285678112
Kurtosis-0.3775599802
Mean-71.06615082
Median Absolute Deviation (MAD)0.0089
Skewness-0.3544419903
Sum-49253888.21
Variance0.0004121729822
MonotonicityNot monotonic
2023-06-03T22:29:57.485796image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
-71.0542 98690
14.2%
-71.0631 95146
13.7%
-71.033 88546
12.8%
-71.081 61216
8.8%
-71.0643 61191
8.8%
-71.1054 54713
7.9%
-71.0551 50891
7.3%
-71.0661 42456
6.1%
-71.1003 42218
6.1%
-71.0707 42048
6.1%
Other values (2) 55956
8.1%
ValueCountFrequency (%)
-71.1054 54713
7.9%
-71.1003 42218
6.1%
-71.0892 29748
4.3%
-71.081 61216
8.8%
-71.0707 42048
6.1%
ValueCountFrequency (%)
-71.033 88546
12.8%
-71.0542 98690
14.2%
-71.055 26208
 
3.8%
-71.0551 50891
7.3%
-71.0631 95146
13.7%

temperature
Real number (ℝ)

Distinct308
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39.58438847
Minimum18.91
Maximum57.22
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:29:57.597994image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum18.91
5-th percentile27.41
Q136.45
median40.49
Q343.58
95-th percentile49.5
Maximum57.22
Range38.31
Interquartile range (IQR)7.13

Descriptive statistics

Standard deviation6.726084129
Coefficient of variation (CV)0.169917596
Kurtosis0.7595186485
Mean39.58438847
Median Absolute Deviation (MAD)3.44
Skewness-0.6090401296
Sum27434791.7
Variance45.24020771
MonotonicityNot monotonic
2023-06-03T22:29:57.714089image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.92 6552
 
0.9%
39.41 5616
 
0.8%
40.13 5616
 
0.8%
38.42 5460
 
0.8%
41.47 5304
 
0.8%
39.35 5304
 
0.8%
35.54 4992
 
0.7%
35.98 4992
 
0.7%
36.53 4992
 
0.7%
40.92 4992
 
0.7%
Other values (298) 639251
92.2%
ValueCountFrequency (%)
18.91 1716
0.2%
18.97 1871
0.3%
19.28 1872
0.3%
20.01 1872
0.3%
20.07 1872
0.3%
ValueCountFrequency (%)
57.22 1872
0.3%
54.62 1872
0.3%
54.59 1872
0.3%
54.38 1872
0.3%
53.51 1872
0.3%

apparentTemperature
Real number (ℝ)

Distinct319
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.88122191
Minimum12.13
Maximum57.22
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:29:57.833447image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum12.13
5-th percentile19.09
Q131.91
median35.9
Q340.08
95-th percentile48.83
Maximum57.22
Range45.09
Interquartile range (IQR)8.17

Descriptive statistics

Standard deviation7.918706819
Coefficient of variation (CV)0.2206922283
Kurtosis1.136294907
Mean35.88122191
Median Absolute Deviation (MAD)4.04
Skewness-0.3937748418
Sum24868234.35
Variance62.70591768
MonotonicityNot monotonic
2023-06-03T22:29:57.948033image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.81 5616
 
0.8%
32.45 5460
 
0.8%
33 5304
 
0.8%
35.66 5304
 
0.8%
34.01 4992
 
0.7%
34.59 4992
 
0.7%
31.03 4992
 
0.7%
35.84 4992
 
0.7%
29.99 4992
 
0.7%
37.54 4992
 
0.7%
Other values (309) 641435
92.5%
ValueCountFrequency (%)
12.13 1872
0.3%
12.26 1872
0.3%
12.65 1872
0.3%
13.25 1872
0.3%
13.84 1871
0.3%
ValueCountFrequency (%)
57.22 1872
0.3%
54.62 1872
0.3%
54.59 1872
0.3%
54.38 1872
0.3%
53.51 1872
0.3%
Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.3 MiB
2023-06-03T22:29:58.052563image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length18
Median length15
Mean length11.7824725
Min length6

Characters and Unicode

Total characters8166090
Distinct characters27
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row Mostly Cloudy
2nd row Rain
3rd row Clear
4th row Clear
5th row Partly Cloudy
ValueCountFrequency (%)
cloudy 273434
26.3%
overcast 218895
21.0%
mostly 146210
14.1%
partly 127224
12.2%
clear 87126
 
8.4%
rain 78624
 
7.6%
light 54912
 
5.3%
drizzle 25932
 
2.5%
possible 18636
 
1.8%
foggy 9060
 
0.9%
2023-06-03T22:29:58.263660image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1733124
21.2%
l 678562
 
8.3%
y 555928
 
6.8%
t 547241
 
6.7%
a 511869
 
6.3%
r 459177
 
5.6%
o 447340
 
5.5%
s 402377
 
4.9%
C 360560
 
4.4%
e 350589
 
4.3%
Other values (17) 2119323
26.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5392913
66.0%
Space Separator 1733124
 
21.2%
Uppercase Letter 1040053
 
12.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
l 678562
12.6%
y 555928
10.3%
t 547241
10.1%
a 511869
9.5%
r 459177
8.5%
o 447340
8.3%
s 402377
7.5%
e 350589
 
6.5%
u 273434
 
5.1%
d 273434
 
5.1%
Other values (8) 892962
16.6%
Uppercase Letter
ValueCountFrequency (%)
C 360560
34.7%
O 218895
21.0%
M 146210
14.1%
P 145860
14.0%
R 78624
 
7.6%
L 54912
 
5.3%
D 25932
 
2.5%
F 9060
 
0.9%
Space Separator
ValueCountFrequency (%)
1733124
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6432966
78.8%
Common 1733124
 
21.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
l 678562
 
10.5%
y 555928
 
8.6%
t 547241
 
8.5%
a 511869
 
8.0%
r 459177
 
7.1%
o 447340
 
7.0%
s 402377
 
6.3%
C 360560
 
5.6%
e 350589
 
5.4%
u 273434
 
4.3%
Other values (16) 1845889
28.7%
Common
ValueCountFrequency (%)
1733124
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8166090
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1733124
21.2%
l 678562
 
8.3%
y 555928
 
6.8%
t 547241
 
6.7%
a 511869
 
6.3%
r 459177
 
5.6%
o 447340
 
5.5%
s 402377
 
4.9%
C 360560
 
4.4%
e 350589
 
4.3%
Other values (17) 2119323
26.0%
Distinct11
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.3 MiB
2023-06-03T22:29:58.385222image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length52
Median length35
Mean length33.70436362
Min length23

Characters and Unicode

Total characters23359517
Distinct characters29
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row Rain throughout the day.
2nd row Rain until morning, starting again in the evening.
3rd row Light rain in the morning.
4th row Partly cloudy throughout the day.
5th row Mostly cloudy throughout the day.
ValueCountFrequency (%)
the 657503
18.4%
throughout 409395
11.5%
day 409395
11.5%
cloudy 347619
9.7%
rain 291320
8.2%
in 248108
 
7.0%
morning 248108
 
7.0%
mostly 202340
 
5.7%
light 188597
 
5.3%
partly 145279
 
4.1%
Other values (11) 420960
11.8%
2023-06-03T22:29:58.607277image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4261695
18.2%
t 2250406
 
9.6%
h 1715434
 
7.3%
o 1715053
 
7.3%
n 1484603
 
6.4%
i 1293281
 
5.5%
u 1249908
 
5.4%
g 1165549
 
5.0%
y 1149405
 
4.9%
r 1099718
 
4.7%
Other values (19) 5974465
25.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 17663749
75.6%
Space Separator 4261695
 
18.2%
Other Punctuation 741002
 
3.2%
Uppercase Letter 693071
 
3.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 2250406
12.7%
h 1715434
9.7%
o 1715053
9.7%
n 1484603
8.4%
i 1293281
 
7.3%
u 1249908
 
7.1%
g 1165549
 
6.6%
y 1149405
 
6.5%
r 1099718
 
6.2%
a 1048827
 
5.9%
Other values (10) 3491565
19.8%
Uppercase Letter
ValueCountFrequency (%)
M 202340
29.2%
L 188597
27.2%
P 147151
21.2%
R 102723
14.8%
F 44772
 
6.5%
O 7488
 
1.1%
Other Punctuation
ValueCountFrequency (%)
. 693071
93.5%
, 47931
 
6.5%
Space Separator
ValueCountFrequency (%)
4261695
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 18356820
78.6%
Common 5002697
 
21.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 2250406
12.3%
h 1715434
9.3%
o 1715053
9.3%
n 1484603
 
8.1%
i 1293281
 
7.0%
u 1249908
 
6.8%
g 1165549
 
6.3%
y 1149405
 
6.3%
r 1099718
 
6.0%
a 1048827
 
5.7%
Other values (16) 4184636
22.8%
Common
ValueCountFrequency (%)
4261695
85.2%
. 693071
 
13.9%
, 47931
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23359517
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4261695
18.2%
t 2250406
 
9.6%
h 1715434
 
7.3%
o 1715053
 
7.3%
n 1484603
 
6.4%
i 1293281
 
5.5%
u 1249908
 
5.4%
g 1165549
 
5.0%
y 1149405
 
4.9%
r 1099718
 
4.7%
Other values (19) 5974465
25.6%

precipIntensity
Real number (ℝ)

Distinct63
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.008922152564
Minimum0
Maximum0.1447
Zeros542243
Zeros (%)78.2%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:29:58.730300image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0.0786
Maximum0.1447
Range0.1447
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.02690055324
Coefficient of variation (CV)3.015029506
Kurtosis10.37560547
Mean0.008922152564
Median Absolute Deviation (MAD)0
Skewness3.325535589
Sum6183.6852
Variance0.0007236397647
MonotonicityNot monotonic
2023-06-03T22:29:58.839816image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 542243
78.2%
0.002 5616
 
0.8%
0.0005 5424
 
0.8%
0.1058 4056
 
0.6%
0.0013 3744
 
0.5%
0.0024 3552
 
0.5%
0.1264 3432
 
0.5%
0.0021 3360
 
0.5%
0.0772 3120
 
0.5%
0.0274 3120
 
0.5%
Other values (53) 115404
 
16.7%
ValueCountFrequency (%)
0 542243
78.2%
0.0002 1872
 
0.3%
0.0003 3120
 
0.5%
0.0005 5424
 
0.8%
0.0006 1680
 
0.2%
ValueCountFrequency (%)
0.1447 3120
0.5%
0.1299 3120
0.5%
0.1289 1872
0.3%
0.1267 3120
0.5%
0.1264 3432
0.5%

precipProbability
Real number (ℝ)

Distinct29
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.14607577
Minimum0
Maximum1
Zeros542243
Zeros (%)78.2%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:29:58.953327image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3289383563
Coefficient of variation (CV)2.2518338
Kurtosis2.335139756
Mean0.14607577
Median Absolute Deviation (MAD)0
Skewness2.027870168
Sum101240.88
Variance0.1082004422
MonotonicityNot monotonic
2023-06-03T22:29:59.049839image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0 542243
78.2%
1 71760
 
10.4%
0.29 5424
 
0.8%
0.03 5424
 
0.8%
0.32 4992
 
0.7%
0.94 4992
 
0.7%
0.14 3744
 
0.5%
0.59 3744
 
0.5%
0.74 3744
 
0.5%
0.1 3552
 
0.5%
Other values (19) 43452
 
6.3%
ValueCountFrequency (%)
0 542243
78.2%
0.02 1872
 
0.3%
0.03 5424
 
0.8%
0.07 1872
 
0.3%
0.09 3552
 
0.5%
ValueCountFrequency (%)
1 71760
10.4%
0.99 1872
 
0.3%
0.94 4992
 
0.7%
0.86 1680
 
0.2%
0.85 1872
 
0.3%

humidity
Real number (ℝ)

Distinct51
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.7411186877
Minimum0.38
Maximum0.96
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:29:59.153378image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.38
5-th percentile0.52
Q10.64
median0.71
Q30.88
95-th percentile0.94
Maximum0.96
Range0.58
Interquartile range (IQR)0.24

Descriptive statistics

Standard deviation0.1385949133
Coefficient of variation (CV)0.1870077163
Kurtosis-1.028075121
Mean0.7411186877
Median Absolute Deviation (MAD)0.11
Skewness-0.07539532214
Sum513647.87
Variance0.01920855
MonotonicityNot monotonic
2023-06-03T22:29:59.391452image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.69 36972
 
5.3%
0.91 36543
 
5.3%
0.7 36453
 
5.3%
0.92 30000
 
4.3%
0.71 28073
 
4.1%
0.64 26520
 
3.8%
0.93 25884
 
3.7%
0.94 22776
 
3.3%
0.65 21683
 
3.1%
0.6 19499
 
2.8%
Other values (41) 408668
59.0%
ValueCountFrequency (%)
0.38 624
 
0.1%
0.4 1872
 
0.3%
0.41 1872
 
0.3%
0.44 3134
0.5%
0.46 5602
0.8%
ValueCountFrequency (%)
0.96 11232
 
1.6%
0.95 13104
1.9%
0.94 22776
3.3%
0.93 25884
3.7%
0.92 30000
4.3%

windSpeed
Real number (ℝ)

Distinct291
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.186252996
Minimum0.45
Maximum15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:29:59.552549image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.45
5-th percentile1.92
Q13.41
median5.91
Q38.41
95-th percentile11.92
Maximum15
Range14.55
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.148222888
Coefficient of variation (CV)0.508906262
Kurtosis-0.5609198841
Mean6.186252996
Median Absolute Deviation (MAD)2.5
Skewness0.4511099449
Sum4287512.55
Variance9.91130735
MonotonicityNot monotonic
2023-06-03T22:29:59.665084image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.33 9048
 
1.3%
8.11 7488
 
1.1%
8.41 7332
 
1.1%
4.54 6708
 
1.0%
8.28 6552
 
0.9%
8.52 6240
 
0.9%
3.02 5616
 
0.8%
9.42 5460
 
0.8%
2.74 5424
 
0.8%
9.63 5304
 
0.8%
Other values (281) 627899
90.6%
ValueCountFrequency (%)
0.45 420
 
0.1%
0.51 84
 
< 0.1%
0.53 672
 
0.1%
1.03 1872
0.3%
1.05 1872
0.3%
ValueCountFrequency (%)
15 1872
0.3%
14.95 1872
0.3%
14.36 1872
0.3%
14.3 1872
0.3%
14.15 1872
0.3%

windGust
Real number (ℝ)

Distinct286
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.469860159
Minimum0.8
Maximum27.25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:29:59.779608image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.8
5-th percentile2.53
Q14.06
median7.55
Q311.74
95-th percentile17.68
Maximum27.25
Range26.45
Interquartile range (IQR)7.68

Descriptive statistics

Standard deviation5.289178729
Coefficient of variation (CV)0.6244706087
Kurtosis1.153693218
Mean8.469860159
Median Absolute Deviation (MAD)3.73
Skewness1.118738999
Sum5870214.45
Variance27.97541162
MonotonicityNot monotonic
2023-06-03T22:29:59.899116image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.47 7488
 
1.1%
12.38 6863
 
1.0%
4.16 5616
 
0.8%
12.21 5616
 
0.8%
3.73 5616
 
0.8%
4.75 5616
 
0.8%
3.48 5616
 
0.8%
11.54 5460
 
0.8%
7.78 5424
 
0.8%
3.49 5424
 
0.8%
Other values (276) 634332
91.5%
ValueCountFrequency (%)
0.8 84
 
< 0.1%
0.87 420
 
0.1%
0.88 672
 
0.1%
1.05 1872
0.3%
1.44 1872
0.3%
ValueCountFrequency (%)
27.25 1872
0.3%
26.67 1872
0.3%
26.56 1872
0.3%
25.75 1872
0.3%
25.17 1872
0.3%

windGustTime
Real number (ℝ)

Distinct25
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1544048884
Minimum1543150800
Maximum1545127200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:30:00.003633image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1543150800
5-th percentile1543287600
Q11543431600
median1543755600
Q31544846400
95-th percentile1545022800
Maximum1545127200
Range1976400
Interquartile range (IQR)1414800

Descriptive statistics

Standard deviation692824.4023
Coefficient of variation (CV)0.0004487062616
Kurtosis-1.59662828
Mean1544048884
Median Absolute Deviation (MAD)417600
Skewness0.4390095435
Sum1.070135504 × 1015
Variance4.800056524 × 1011
MonotonicityNot monotonic
2023-06-03T22:30:00.108186image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
1543431600 79619
 
11.5%
1543338000 49920
 
7.2%
1545015600 44928
 
6.5%
1544846400 44928
 
6.5%
1544918400 44928
 
6.5%
1543672800 44928
 
6.5%
1545022800 44928
 
6.5%
1543755600 44928
 
6.5%
1544738400 44771
 
6.5%
1543514400 44581
 
6.4%
Other values (15) 204612
29.5%
ValueCountFrequency (%)
1543150800 504
 
0.1%
1543287600 37767
5.4%
1543291200 10164
 
1.5%
1543305600 3113
 
0.4%
1543334400 10140
 
1.5%
ValueCountFrequency (%)
1545127200 26832
3.9%
1545022800 44928
6.5%
1545015600 44928
6.5%
1544918400 44928
6.5%
1544846400 44928
6.5%

visibility
Real number (ℝ)

Distinct227
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.46797045
Minimum0.717
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:30:00.229219image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.717
5-th percentile2.683
Q18.432
median9.88
Q39.996
95-th percentile10
Maximum10
Range9.283
Interquartile range (IQR)1.564

Descriptive statistics

Standard deviation2.60288815
Coefficient of variation (CV)0.3073804007
Kurtosis0.6368939765
Mean8.46797045
Median Absolute Deviation (MAD)0.12
Skewness-1.507075391
Sum5868904.748
Variance6.775026721
MonotonicityNot monotonic
2023-06-03T22:30:00.339728image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10 167102
 
24.1%
9.933 8736
 
1.3%
9.972 7758
 
1.1%
9.908 6864
 
1.0%
9.961 6864
 
1.0%
9.974 6864
 
1.0%
9.996 6240
 
0.9%
9.725 5616
 
0.8%
9.92 5616
 
0.8%
9.706 5616
 
0.8%
Other values (217) 465795
67.2%
ValueCountFrequency (%)
0.717 1872
0.3%
0.965 1680
0.2%
1.348 1872
0.3%
1.413 1872
0.3%
1.46 1872
0.3%
ValueCountFrequency (%)
10 167102
24.1%
9.997 1872
 
0.3%
9.996 6240
 
0.9%
9.995 1872
 
0.3%
9.994 1872
 
0.3%

temperatureHigh
Real number (ℝ)

Distinct129
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45.04098166
Minimum32.68
Maximum57.87
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:30:00.451267image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum32.68
5-th percentile33.78
Q142.57
median44.68
Q346.91
95-th percentile57.04
Maximum57.87
Range25.19
Interquartile range (IQR)4.34

Descriptive statistics

Standard deviation5.99654115
Coefficient of variation (CV)0.1331352233
Kurtosis0.1573075002
Mean45.04098166
Median Absolute Deviation (MAD)2.21
Skewness0.07621844773
Sum31216598.2
Variance35.95850576
MonotonicityNot monotonic
2023-06-03T22:30:00.593809image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
42.6 28079
 
4.1%
42.61 27300
 
3.9%
44.66 14962
 
2.2%
42.18 14925
 
2.2%
42.57 14724
 
2.1%
46.49 14664
 
2.1%
54.47 13104
 
1.9%
54.29 13104
 
1.9%
47.11 12480
 
1.8%
41.44 11232
 
1.6%
Other values (119) 528497
76.3%
ValueCountFrequency (%)
32.68 1872
 
0.3%
32.75 3744
0.5%
32.8 5616
0.8%
32.81 5616
0.8%
32.84 5616
0.8%
ValueCountFrequency (%)
57.87 11232
1.6%
57.52 5616
0.8%
57.42 5616
0.8%
57.27 7488
1.1%
57.08 3744
 
0.5%

temperatureHighTime
Real number (ℝ)

Distinct23
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1544049895
Minimum1543154400
Maximum1545159600
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:30:00.700330image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1543154400
5-th percentile1543255200
Q11543438800
median1543788000
Q31544814000
95-th percentile1545076800
Maximum1545159600
Range2005200
Interquartile range (IQR)1375200

Descriptive statistics

Standard deviation693792.1075
Coefficient of variation (CV)0.0004493326996
Kurtosis-1.557936158
Mean1544049895
Median Absolute Deviation (MAD)468000
Skewness0.4298924388
Sum1.070136205 × 1015
Variance4.813474884 × 1011
MonotonicityNot monotonic
2023-06-03T22:30:00.800853image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
1543438800 79619
11.5%
1543320000 63173
 
9.1%
1543600800 45396
 
6.5%
1544814000 44928
 
6.5%
1544896800 44928
 
6.5%
1543690800 44928
 
6.5%
1545076800 44928
 
6.5%
1543852800 44772
 
6.5%
1544731200 44771
 
6.5%
1543510800 44581
 
6.4%
Other values (13) 191047
27.6%
ValueCountFrequency (%)
1543154400 504
 
0.1%
1543251600 10164
 
1.5%
1543255200 37767
5.4%
1543320000 63173
9.1%
1543420800 14925
 
2.2%
ValueCountFrequency (%)
1545159600 26832
3.9%
1545076800 44928
6.5%
1544990400 41184
5.9%
1544968800 3744
 
0.5%
1544896800 44928
6.5%

temperatureLow
Real number (ℝ)

Distinct133
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.15073558
Minimum17.85
Maximum46.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:30:00.915146image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum17.85
5-th percentile21.79
Q130.17
median34.18
Q338.73
95-th percentile44.88
Maximum46.6
Range28.75
Interquartile range (IQR)8.56

Descriptive statistics

Standard deviation6.383163384
Coefficient of variation (CV)0.1869114464
Kurtosis-0.4216659797
Mean34.15073558
Median Absolute Deviation (MAD)4.31
Skewness-0.334682542
Sum23668884.46
Variance40.74477479
MonotonicityNot monotonic
2023-06-03T22:30:01.015711image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.6 20436
 
2.9%
37.44 14976
 
2.2%
36.71 14925
 
2.2%
41.9 14664
 
2.1%
27.05 13104
 
1.9%
37.33 13103
 
1.9%
33.85 12480
 
1.8%
33.6 11856
 
1.7%
35.04 11232
 
1.6%
32.8 11232
 
1.6%
Other values (123) 555063
80.1%
ValueCountFrequency (%)
17.85 1262
 
0.2%
18.31 1858
0.3%
19.36 1872
0.3%
19.63 1560
0.2%
20.66 3744
0.5%
ValueCountFrequency (%)
46.6 9360
1.4%
45.04 7488
1.1%
44.99 3744
 
0.5%
44.97 7488
1.1%
44.96 5616
0.8%

temperatureLowTime
Real number (ℝ)

Distinct31
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1544102171
Minimum1543233600
Maximum1545220800
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:30:01.118279image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1543233600
5-th percentile1543298400
Q11543489200
median1543816800
Q31544835600
95-th percentile1545138000
Maximum1545220800
Range1987200
Interquartile range (IQR)1346400

Descriptive statistics

Standard deviation692292.332
Coefficient of variation (CV)0.0004483461943
Kurtosis-1.546919293
Mean1544102171
Median Absolute Deviation (MAD)417600
Skewness0.4415329241
Sum1.070172436 × 1015
Variance4.792686729 × 1011
MonotonicityNot monotonic
2023-06-03T22:30:01.219773image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
1543489200 57311
 
8.3%
1543399200 53033
 
7.7%
1543298400 47931
 
6.9%
1544954400 44928
 
6.5%
1543712400 44928
 
6.5%
1543921200 44772
 
6.5%
1545044400 41184
 
5.9%
1543816800 35568
 
5.1%
1543579200 35235
 
5.1%
1544781600 33695
 
4.9%
Other values (21) 254486
36.7%
ValueCountFrequency (%)
1543233600 504
 
0.1%
1543298400 47931
6.9%
1543399200 53033
7.7%
1543402800 10140
 
1.5%
1543464000 8268
 
1.2%
ValueCountFrequency (%)
1545220800 26832
3.9%
1545138000 24336
3.5%
1545134400 14976
2.2%
1545130800 5616
 
0.8%
1545048000 3744
 
0.5%

apparentTemperatureHigh
Real number (ℝ)

Distinct124
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41.61405403
Minimum22.62
Maximum57.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:30:01.334302image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum22.62
5-th percentile31.62
Q136.57
median40.95
Q344.12
95-th percentile56.37
Maximum57.2
Range34.58
Interquartile range (IQR)7.55

Descriptive statistics

Standard deviation7.666137513
Coefficient of variation (CV)0.1842199154
Kurtosis0.1496288356
Mean41.61405403
Median Absolute Deviation (MAD)4.2
Skewness0.06981074397
Sum28841494.04
Variance58.76966437
MonotonicityNot monotonic
2023-06-03T22:30:01.443842image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.57 20436
 
2.9%
43.84 18408
 
2.7%
43.85 18096
 
2.6%
36.58 14976
 
2.2%
35.95 14976
 
2.2%
32.95 14976
 
2.2%
35.75 14925
 
2.2%
53.8 13104
 
1.9%
53.62 13104
 
1.9%
38.39 13104
 
1.9%
Other values (114) 536966
77.5%
ValueCountFrequency (%)
22.62 1872
 
0.3%
22.69 5616
0.8%
22.75 7488
1.1%
22.77 1872
 
0.3%
22.87 3744
0.5%
ValueCountFrequency (%)
57.2 11232
1.6%
56.85 5616
0.8%
56.75 5616
0.8%
56.6 7488
1.1%
56.41 3744
 
0.5%
Distinct27
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1544050235
Minimum1543186800
Maximum1545159600
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:30:01.564370image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1543186800
5-th percentile1543251600
Q11543438800
median1543788000
Q31544817600
95-th percentile1545076800
Maximum1545159600
Range1972800
Interquartile range (IQR)1378800

Descriptive statistics

Standard deviation694169.8738
Coefficient of variation (CV)0.0004495772598
Kurtosis-1.558545897
Mean1544050235
Median Absolute Deviation (MAD)468000
Skewness0.426763305
Sum1.070136441 × 1015
Variance4.818718137 × 1011
MonotonicityNot monotonic
2023-06-03T22:30:01.668860image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
1543438800 66360
 
9.6%
1543320000 63173
 
9.1%
1543690800 44928
 
6.5%
1544817600 44928
 
6.5%
1544896800 44928
 
6.5%
1543852800 44772
 
6.5%
1543510800 44581
 
6.4%
1544986800 41184
 
5.9%
1543788000 41184
 
5.9%
1545076800 39312
 
5.7%
Other values (17) 217721
31.4%
ValueCountFrequency (%)
1543186800 504
 
0.1%
1543244400 22980
 
3.3%
1543251600 24951
 
3.6%
1543320000 63173
9.1%
1543420800 14925
 
2.2%
ValueCountFrequency (%)
1545159600 26832
3.9%
1545080400 5616
 
0.8%
1545076800 39312
5.7%
1544986800 41184
5.9%
1544968800 3744
 
0.5%

apparentTemperatureLow
Real number (ℝ)

Distinct136
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30.1398238
Minimum11.81
Maximum47.25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:30:01.788402image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum11.81
5-th percentile12.05
Q127.7
median30.03
Q335.32
95-th percentile45.53
Maximum47.25
Range35.44
Interquartile range (IQR)7.62

Descriptive statistics

Standard deviation8.057468112
Coefficient of variation (CV)0.2673362713
Kurtosis0.5212626254
Mean30.1398238
Median Absolute Deviation (MAD)3.83
Skewness-0.5012408847
Sum20889037.82
Variance64.92279237
MonotonicityNot monotonic
2023-06-03T22:30:01.902972image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
32.12 20436
 
2.9%
31.97 14976
 
2.2%
30.29 14925
 
2.2%
36.7 14664
 
2.1%
28.06 13104
 
1.9%
31.82 13103
 
1.9%
30.03 12480
 
1.8%
35.08 11232
 
1.6%
27.22 11232
 
1.6%
35.32 11232
 
1.6%
Other values (126) 555687
80.2%
ValueCountFrequency (%)
11.81 3744
0.5%
11.82 7488
1.1%
11.83 7488
1.1%
11.84 3744
0.5%
11.86 1872
 
0.3%
ValueCountFrequency (%)
47.25 9360
1.4%
45.69 7488
1.1%
45.64 3744
 
0.5%
45.62 7488
1.1%
45.61 5616
0.8%
Distinct32
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1544098720
Minimum1543233600
Maximum1545199200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:30:02.033065image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1543233600
5-th percentile1543298400
Q11543478400
median1543816800
Q31544835600
95-th percentile1545134400
Maximum1545199200
Range1965600
Interquartile range (IQR)1357200

Descriptive statistics

Standard deviation692737.8252
Coefficient of variation (CV)0.0004486357096
Kurtosis-1.556258065
Mean1544098720
Median Absolute Deviation (MAD)417600
Skewness0.4374113797
Sum1.070170044 × 1015
Variance4.798856944 × 1011
MonotonicityNot monotonic
2023-06-03T22:30:02.189647image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
1543478400 71351
 
10.3%
1543399200 53033
 
7.7%
1545044400 44928
 
6.5%
1544835600 44928
 
6.5%
1543712400 44928
 
6.5%
1545134400 44928
 
6.5%
1543914000 44772
 
6.5%
1543298400 37767
 
5.4%
1543816800 35568
 
5.1%
1543658400 32292
 
4.7%
Other values (22) 238576
34.4%
ValueCountFrequency (%)
1543233600 504
 
0.1%
1543291200 10164
 
1.5%
1543298400 37767
5.4%
1543392000 10140
 
1.5%
1543399200 53033
7.7%
ValueCountFrequency (%)
1545199200 16848
 
2.4%
1545195600 9984
 
1.4%
1545134400 44928
6.5%
1545044400 44928
6.5%
1544954400 22464
3.2%

icon
Text

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.3 MiB
2023-06-03T22:30:02.339692image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length21
Median length19
Mean length13.00599217
Min length5

Characters and Unicode

Total characters9014076
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row partly-cloudy-night
2nd row rain
3rd row clear-night
4th row clear-night
5th row partly-cloudy-night
ValueCountFrequency (%)
cloudy 218895
31.6%
partly-cloudy-night 158030
22.8%
partly-cloudy-day 115404
16.7%
rain 104556
15.1%
clear-night 60294
 
8.7%
clear-day 26832
 
3.9%
fog 9060
 
1.3%
2023-06-03T22:30:02.585410image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1386142
15.4%
y 907999
10.1%
l 852889
9.5%
d 634565
 
7.0%
- 633994
 
7.0%
a 607352
 
6.7%
c 579455
 
6.4%
o 501389
 
5.6%
u 492329
 
5.5%
t 491758
 
5.5%
Other values (8) 1926204
21.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6993940
77.6%
Space Separator 1386142
 
15.4%
Dash Punctuation 633994
 
7.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
y 907999
13.0%
l 852889
12.2%
d 634565
9.1%
a 607352
8.7%
c 579455
8.3%
o 501389
7.2%
u 492329
7.0%
t 491758
7.0%
r 465116
6.7%
n 322880
 
4.6%
Other values (6) 1138208
16.3%
Space Separator
ValueCountFrequency (%)
1386142
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 633994
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6993940
77.6%
Common 2020136
 
22.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
y 907999
13.0%
l 852889
12.2%
d 634565
9.1%
a 607352
8.7%
c 579455
8.3%
o 501389
7.2%
u 492329
7.0%
t 491758
7.0%
r 465116
6.7%
n 322880
 
4.6%
Other values (6) 1138208
16.3%
Common
ValueCountFrequency (%)
1386142
68.6%
- 633994
31.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9014076
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1386142
15.4%
y 907999
10.1%
l 852889
9.5%
d 634565
 
7.0%
- 633994
 
7.0%
a 607352
 
6.7%
c 579455
 
6.4%
o 501389
 
5.6%
u 492329
 
5.5%
t 491758
 
5.5%
Other values (8) 1926204
21.4%

dewPoint
Real number (ℝ)

Distinct313
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.65625601
Minimum4.39
Maximum50.67
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:30:02.907075image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum4.39
5-th percentile10.79
Q127.49
median30.69
Q338.12
95-th percentile45.86
Maximum50.67
Range46.28
Interquartile range (IQR)10.63

Descriptive statistics

Standard deviation9.142355285
Coefficient of variation (CV)0.2888009018
Kurtosis0.4293608902
Mean31.65625601
Median Absolute Deviation (MAD)4.12
Skewness-0.49834523
Sum21940033.01
Variance83.58266016
MonotonicityNot monotonic
2023-06-03T22:30:03.089099image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
28.39 8736
 
1.3%
30.16 7488
 
1.1%
28.36 5460
 
0.8%
30.3 5460
 
0.8%
29.86 5304
 
0.8%
28.91 4992
 
0.7%
29.27 4992
 
0.7%
29.57 4992
 
0.7%
27.26 4992
 
0.7%
28.14 4992
 
0.7%
Other values (303) 635663
91.7%
ValueCountFrequency (%)
4.39 1262
0.2%
5.3 1858
0.3%
6.46 1872
0.3%
6.89 1872
0.3%
7.06 1716
0.2%
ValueCountFrequency (%)
50.67 1872
0.3%
49.27 1872
0.3%
48.63 1872
0.3%
48.54 1872
0.3%
48.02 1872
0.3%

pressure
Real number (ℝ)

Distinct316
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1010.094766
Minimum988.09
Maximum1035.55
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:30:03.283200image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum988.09
5-th percentile991.05
Q1999.82
median1009.25
Q31021.86
95-th percentile1033.94
Maximum1035.55
Range47.46
Interquartile range (IQR)22.04

Descriptive statistics

Standard deviation13.4728994
Coefficient of variation (CV)0.01333825286
Kurtosis-1.084371182
Mean1010.094766
Median Absolute Deviation (MAD)11.29
Skewness0.1542240584
Sum700067389.9
Variance181.5190184
MonotonicityNot monotonic
2023-06-03T22:30:03.472287image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
996.21 5616
 
0.8%
996.92 5460
 
0.8%
991.46 5363
 
0.8%
995.3 5304
 
0.8%
991.36 4992
 
0.7%
994.99 4992
 
0.7%
991.33 4992
 
0.7%
991.21 4992
 
0.7%
991.71 4992
 
0.7%
991.07 4992
 
0.7%
Other values (306) 641376
92.5%
ValueCountFrequency (%)
988.09 3120
0.5%
988.29 3120
0.5%
988.3 3120
0.5%
988.85 3120
0.5%
989.46 3120
0.5%
ValueCountFrequency (%)
1035.55 1872
0.3%
1035.42 1872
0.3%
1035.3 1872
0.3%
1035.14 1872
0.3%
1035.06 1872
0.3%

windBearing
Real number (ℝ)

Distinct195
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean220.0558529
Minimum2
Maximum356
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:30:03.615361image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile44
Q1124
median258
Q3303
95-th percentile339
Maximum356
Range354
Interquartile range (IQR)179

Descriptive statistics

Standard deviation99.10273601
Coefficient of variation (CV)0.4503526478
Kurtosis-1.028233886
Mean220.0558529
Median Absolute Deviation (MAD)55
Skewness-0.6259414418
Sum152514330
Variance9821.352285
MonotonicityNot monotonic
2023-06-03T22:30:03.781898image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
303 18669
 
2.7%
295 15444
 
2.2%
297 15443
 
2.2%
313 12927
 
1.9%
294 11232
 
1.6%
296 10608
 
1.5%
305 10296
 
1.5%
310 9828
 
1.4%
306 9360
 
1.4%
314 9346
 
1.3%
Other values (185) 569918
82.2%
ValueCountFrequency (%)
2 3552
0.5%
13 3744
0.5%
16 1872
0.3%
18 1872
0.3%
19 1680
0.2%
ValueCountFrequency (%)
356 1872
0.3%
353 1716
0.2%
352 1872
0.3%
350 1872
0.3%
349 3744
0.5%

cloudCover
Real number (ℝ)

Distinct83
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.6865020467
Minimum0
Maximum1
Zeros39547
Zeros (%)5.7%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:30:04.022077image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.37
median0.82
Q31
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0.63

Descriptive statistics

Standard deviation0.3585343607
Coefficient of variation (CV)0.5222626245
Kurtosis-0.9983778444
Mean0.6865020467
Median Absolute Deviation (MAD)0.18
Skewness-0.7331299906
Sum475794.66
Variance0.1285468878
MonotonicityNot monotonic
2023-06-03T22:30:04.223160image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 267927
38.7%
0 39547
 
5.7%
0.81 19344
 
2.8%
0.77 16068
 
2.3%
0.99 14352
 
2.1%
0.44 11493
 
1.7%
0.25 11076
 
1.6%
0.12 10764
 
1.6%
0.37 10608
 
1.5%
0.54 10608
 
1.5%
Other values (73) 281284
40.6%
ValueCountFrequency (%)
0 39547
5.7%
0.01 4368
 
0.6%
0.02 7487
 
1.1%
0.03 6396
 
0.9%
0.04 5616
 
0.8%
ValueCountFrequency (%)
1 267927
38.7%
0.99 14352
 
2.1%
0.98 5616
 
0.8%
0.97 2184
 
0.3%
0.96 3744
 
0.5%

uvIndex
Real number (ℝ)

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2489081205
Minimum0
Maximum2
Zeros533664
Zeros (%)77.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:30:04.346690image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum2
Range2
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.4740965092
Coefficient of variation (CV)1.904704869
Kurtosis1.907124905
Mean0.2489081205
Median Absolute Deviation (MAD)0
Skewness1.680640279
Sum172511
Variance0.2247675
MonotonicityNot monotonic
2023-06-03T22:30:04.484233image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=3)
ValueCountFrequency (%)
0 533664
77.0%
1 146303
 
21.1%
2 13104
 
1.9%
ValueCountFrequency (%)
0 533664
77.0%
1 146303
 
21.1%
2 13104
 
1.9%
ValueCountFrequency (%)
2 13104
 
1.9%
1 146303
 
21.1%
0 533664
77.0%

visibility.1
Real number (ℝ)

Distinct227
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.46797045
Minimum0.717
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:30:04.655121image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.717
5-th percentile2.683
Q18.432
median9.88
Q39.996
95-th percentile10
Maximum10
Range9.283
Interquartile range (IQR)1.564

Descriptive statistics

Standard deviation2.60288815
Coefficient of variation (CV)0.3073804007
Kurtosis0.6368939765
Mean8.46797045
Median Absolute Deviation (MAD)0.12
Skewness-1.507075391
Sum5868904.748
Variance6.775026721
MonotonicityNot monotonic
2023-06-03T22:30:04.831176image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10 167102
 
24.1%
9.933 8736
 
1.3%
9.972 7758
 
1.1%
9.908 6864
 
1.0%
9.961 6864
 
1.0%
9.974 6864
 
1.0%
9.996 6240
 
0.9%
9.725 5616
 
0.8%
9.92 5616
 
0.8%
9.706 5616
 
0.8%
Other values (217) 465795
67.2%
ValueCountFrequency (%)
0.717 1872
0.3%
0.965 1680
0.2%
1.348 1872
0.3%
1.413 1872
0.3%
1.46 1872
0.3%
ValueCountFrequency (%)
10 167102
24.1%
9.997 1872
 
0.3%
9.996 6240
 
0.9%
9.995 1872
 
0.3%
9.994 1872
 
0.3%

ozone
Real number (ℝ)

Distinct274
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean313.513635
Minimum269.4
Maximum378.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:30:05.059271image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum269.4
5-th percentile273.9
Q1290.9
median307.4
Q3331.8
95-th percentile364.1
Maximum378.9
Range109.5
Interquartile range (IQR)40.9

Descriptive statistics

Standard deviation27.95306065
Coefficient of variation (CV)0.08916058995
Kurtosis-0.8654050456
Mean313.513635
Median Absolute Deviation (MAD)19.5
Skewness0.4148479696
Sum217287208.5
Variance781.3735998
MonotonicityNot monotonic
2023-06-03T22:30:05.235398image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
290.3 8736
 
1.3%
355 8580
 
1.2%
291.1 6864
 
1.0%
299.7 5616
 
0.8%
273.9 5616
 
0.8%
352.8 5616
 
0.8%
274.6 5616
 
0.8%
326.9 5616
 
0.8%
296 5616
 
0.8%
325.3 5616
 
0.8%
Other values (264) 629579
90.8%
ValueCountFrequency (%)
269.4 1872
0.3%
269.6 1872
0.3%
269.8 1872
0.3%
269.9 1872
0.3%
270.1 1872
0.3%
ValueCountFrequency (%)
378.9 1872
0.3%
378.7 1872
0.3%
377.1 1872
0.3%
376.9 1872
0.3%
376.8 1872
0.3%

sunriseTime
Real number (ℝ)

Distinct110
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1544027098
Minimum1543146535
Maximum1545135001
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:30:05.379945image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1543146535
5-th percentile1543233003
Q11543405938
median1543751761
Q31544789239
95-th percentile1545048561
Maximum1545135001
Range1988466
Interquartile range (IQR)1383301

Descriptive statistics

Standard deviation691139.2717
Coefficient of variation (CV)0.000447621206
Kurtosis-1.55992535
Mean1544027098
Median Absolute Deviation (MAD)432290
Skewness0.4343626674
Sum1.070120405 × 1015
Variance4.776734929 × 1011
MonotonicityNot monotonic
2023-06-03T22:30:05.518042image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1543405938 23616
 
3.4%
1543405936 20592
 
3.0%
1543233003 19704
 
2.8%
1544875681 18720
 
2.7%
1544702792 16847
 
2.4%
1545048561 14976
 
2.2%
1543405904 14925
 
2.2%
1544789239 13104
 
1.9%
1543751794 13104
 
1.9%
1544962122 13104
 
1.9%
Other values (100) 524379
75.7%
ValueCountFrequency (%)
1543146535 420
 
0.1%
1543146539 84
 
< 0.1%
1543232969 10164
1.5%
1543232998 1596
 
0.2%
1543233000 9831
1.4%
ValueCountFrequency (%)
1545135001 5616
0.8%
1545134998 3744
 
0.5%
1545134997 7488
1.1%
1545134994 9360
1.4%
1545134992 624
 
0.1%

sunsetTime
Real number (ℝ)

Distinct114
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1544060439
Minimum1543180615
Maximum1545167693
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:30:05.655592image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1543180615
5-th percentile1543266980
Q11543439721
median1543785233
Q31544822019
95-th percentile1545081273
Maximum1545167693
Range1987078
Interquartile range (IQR)1382298

Descriptive statistics

Standard deviation690663.393
Coefficient of variation (CV)0.000447303341
Kurtosis-1.559850056
Mean1544060439
Median Absolute Deviation (MAD)431881
Skewness0.434494196
Sum1.070143512 × 1015
Variance4.770159224 × 1011
MonotonicityNot monotonic
2023-06-03T22:30:05.789131image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1543439719 21743
 
3.1%
1543439716 20436
 
2.9%
1543439718 14976
 
2.2%
1543439738 14925
 
2.2%
1543266973 14664
 
2.1%
1544908425 13104
 
1.9%
1543353345 12480
 
1.8%
1543353343 12480
 
1.8%
1543266976 11511
 
1.7%
1543871641 11232
 
1.6%
Other values (104) 545520
78.7%
ValueCountFrequency (%)
1543180615 420
 
0.1%
1543180617 84
 
< 0.1%
1543266971 1680
 
0.2%
1543266973 14664
2.1%
1543266974 3276
 
0.5%
ValueCountFrequency (%)
1545167693 5616
0.8%
1545167687 3744
0.5%
1545167683 5616
0.8%
1545167681 2496
0.4%
1545167680 3744
0.5%

moonPhase
Real number (ℝ)

Distinct18
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5790655359
Minimum0.09
Maximum0.93
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:30:05.933712image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.09
5-th percentile0.21
Q10.3
median0.68
Q30.79
95-th percentile0.89
Maximum0.93
Range0.84
Interquartile range (IQR)0.49

Descriptive statistics

Standard deviation0.2447052562
Coefficient of variation (CV)0.4225864622
Kurtosis-1.495533474
Mean0.5790655359
Median Absolute Deviation (MAD)0.18
Skewness-0.3795603393
Sum401333.53
Variance0.05988066241
MonotonicityNot monotonic
2023-06-03T22:30:06.022223image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0.72 94544
13.6%
0.68 63173
 
9.1%
0.64 47931
 
6.9%
0.79 45396
 
6.5%
0.3 44928
 
6.5%
0.27 44928
 
6.5%
0.24 44928
 
6.5%
0.33 44928
 
6.5%
0.86 44928
 
6.5%
0.82 44928
 
6.5%
Other values (8) 172459
24.9%
ValueCountFrequency (%)
0.09 4447
 
0.6%
0.18 3120
 
0.5%
0.21 44771
6.5%
0.24 44928
6.5%
0.27 44928
6.5%
ValueCountFrequency (%)
0.93 3432
 
0.5%
0.89 44772
6.5%
0.86 44928
6.5%
0.82 44928
6.5%
0.79 45396
6.5%

precipIntensityMax
Real number (ℝ)

Distinct65
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.03737440868
Minimum0
Maximum0.1459
Zeros228096
Zeros (%)32.9%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:30:06.145547image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.0004
Q30.0916
95-th percentile0.1429
Maximum0.1459
Range0.1459
Interquartile range (IQR)0.0916

Descriptive statistics

Standard deviation0.05521378827
Coefficient of variation (CV)1.477315367
Kurtosis-0.8718140462
Mean0.03737440868
Median Absolute Deviation (MAD)0.0004
Skewness0.9924137676
Sum25903.1188
Variance0.003048562415
MonotonicityNot monotonic
2023-06-03T22:30:06.293939image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 228096
32.9%
0.0001 59696
 
8.6%
0.0004 45240
 
6.5%
0.0003 21295
 
3.1%
0.143 18720
 
2.7%
0.0028 16848
 
2.4%
0.1225 14664
 
2.1%
0.0074 13104
 
1.9%
0.0007 11232
 
1.6%
0.1246 11232
 
1.6%
Other values (55) 252944
36.5%
ValueCountFrequency (%)
0 228096
32.9%
0.0001 59696
 
8.6%
0.0003 21295
 
3.1%
0.0004 45240
 
6.5%
0.0005 9360
 
1.4%
ValueCountFrequency (%)
0.1459 420
 
0.1%
0.1438 3113
 
0.4%
0.1433 9360
1.4%
0.143 18720
2.7%
0.1429 3120
 
0.5%

uvIndexTime
Real number (ℝ)

Distinct20
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1544043966
Minimum1543161600
Maximum1545152400
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:30:06.441043image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1543161600
5-th percentile1543251600
Q11543420800
median1543770000
Q31544806800
95-th percentile1545066000
Maximum1545152400
Range1990800
Interquartile range (IQR)1386000

Descriptive statistics

Standard deviation691202.7673
Coefficient of variation (CV)0.0004476574388
Kurtosis-1.559509366
Mean1544043966
Median Absolute Deviation (MAD)432000
Skewness0.4354937398
Sum1.070132096 × 1015
Variance4.777612655 × 1011
MonotonicityNot monotonic
2023-06-03T22:30:06.574576image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
1543420800 94544
13.6%
1543338000 63173
 
9.1%
1543251600 47931
 
6.9%
1543593600 45396
 
6.5%
1544979600 44928
 
6.5%
1544893200 44928
 
6.5%
1544806800 44928
 
6.5%
1545066000 44928
 
6.5%
1543770000 44928
 
6.5%
1543683600 44928
 
6.5%
Other values (10) 172459
24.9%
ValueCountFrequency (%)
1543161600 504
 
0.1%
1543251600 47931
6.9%
1543338000 63173
9.1%
1543420800 94544
13.6%
1543507200 7488
 
1.1%
ValueCountFrequency (%)
1545152400 26832
3.9%
1545066000 44928
6.5%
1544979600 44928
6.5%
1544893200 44928
6.5%
1544806800 44928
6.5%

temperatureMin
Real number (ℝ)

Distinct131
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.45777436
Minimum15.63
Maximum43.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:30:06.719680image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum15.63
5-th percentile18.24
Q130.17
median34.24
Q338.88
95-th percentile42.86
Maximum43.1
Range27.47
Interquartile range (IQR)8.71

Descriptive statistics

Standard deviation6.467224013
Coefficient of variation (CV)0.1932951052
Kurtosis0.2764820484
Mean33.45777436
Median Absolute Deviation (MAD)4.64
Skewness-0.8700806893
Sum23188613.13
Variance41.82498644
MonotonicityNot monotonic
2023-06-03T22:30:06.835253image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.7 21743
 
3.1%
33.85 20436
 
2.9%
36.34 18720
 
2.7%
33.75 14976
 
2.2%
33.1 14925
 
2.2%
40.45 14664
 
2.1%
38.94 13104
 
1.9%
31.71 11232
 
1.6%
34.07 11232
 
1.6%
42.96 11232
 
1.6%
Other values (121) 540807
78.0%
ValueCountFrequency (%)
15.63 156
 
< 0.1%
15.86 1716
0.2%
15.95 1674
0.2%
16.01 901
 
0.1%
17.85 3744
0.5%
ValueCountFrequency (%)
43.1 5460
0.8%
43.09 1872
 
0.3%
42.96 11232
1.6%
42.91 3744
 
0.5%
42.89 5616
0.8%

temperatureMinTime
Real number (ℝ)

Distinct25
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1544041610
Minimum1543122000
Maximum1545192000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:30:07.222447image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1543122000
5-th percentile1543233600
Q11543399200
median1543726800
Q31544788800
95-th percentile1545044400
Maximum1545192000
Range2070000
Interquartile range (IQR)1389600

Descriptive statistics

Standard deviation690195.4414
Coefficient of variation (CV)0.0004470057265
Kurtosis-1.54009665
Mean1544041610
Median Absolute Deviation (MAD)349200
Skewness0.4426259969
Sum1.070130462 × 1015
Variance4.763697473 × 1011
MonotonicityNot monotonic
2023-06-03T22:30:07.343987image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
1543399200 79619
11.5%
1543377600 63173
 
9.1%
1543233600 47931
 
6.9%
1544929200 44928
 
6.5%
1543726800 44928
 
6.5%
1543896000 44772
 
6.5%
1544688000 44771
 
6.5%
1543550400 44581
 
6.4%
1544954400 41184
 
5.9%
1545044400 39312
 
5.7%
Other values (15) 197872
28.6%
ValueCountFrequency (%)
1543122000 504
 
0.1%
1543233600 47931
6.9%
1543377600 63173
9.1%
1543399200 79619
11.5%
1543402800 14925
 
2.2%
ValueCountFrequency (%)
1545192000 26832
3.9%
1545048000 5616
 
0.8%
1545044400 39312
5.7%
1545012000 3744
 
0.5%
1544954400 41184
5.9%

temperatureMax
Real number (ℝ)

Distinct128
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45.26131303
Minimum33.51
Maximum57.87
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:30:07.492528image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum33.51
5-th percentile33.92
Q142.57
median44.68
Q346.91
95-th percentile57.04
Maximum57.87
Range24.36
Interquartile range (IQR)4.34

Descriptive statistics

Standard deviation5.645045689
Coefficient of variation (CV)0.1247212092
Kurtosis0.1974957671
Mean45.26131303
Median Absolute Deviation (MAD)2.17
Skewness0.299476835
Sum31369303.48
Variance31.86654083
MonotonicityNot monotonic
2023-06-03T22:30:07.648583image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
42.6 28079
 
4.1%
42.61 27300
 
3.9%
44.66 14962
 
2.2%
42.18 14925
 
2.2%
42.57 14724
 
2.1%
46.49 14664
 
2.1%
54.47 13104
 
1.9%
54.29 13104
 
1.9%
47.11 12480
 
1.8%
57.87 11232
 
1.6%
Other values (118) 528497
76.3%
ValueCountFrequency (%)
33.51 3588
0.5%
33.62 1872
 
0.3%
33.78 3744
0.5%
33.81 5616
0.8%
33.82 1872
 
0.3%
ValueCountFrequency (%)
57.87 11232
1.6%
57.52 5616
0.8%
57.42 5616
0.8%
57.27 7488
1.1%
57.08 3744
 
0.5%

temperatureMaxTime
Real number (ℝ)

Distinct23
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1544047300
Minimum1543154400
Maximum1545109200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:30:07.764113image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1543154400
5-th percentile1543255200
Q11543438800
median1543788000
Q31544814000
95-th percentile1545076800
Maximum1545109200
Range1954800
Interquartile range (IQR)1375200

Descriptive statistics

Standard deviation690135.3372
Coefficient of variation (CV)0.0004469651527
Kurtosis-1.572471762
Mean1544047300
Median Absolute Deviation (MAD)468000
Skewness0.4230661985
Sum1.070134406 × 1015
Variance4.762867836 × 1011
MonotonicityNot monotonic
2023-06-03T22:30:07.861620image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
1543438800 79619
11.5%
1543320000 63173
 
9.1%
1543600800 45396
 
6.5%
1544896800 44928
 
6.5%
1543690800 44928
 
6.5%
1544814000 44928
 
6.5%
1543852800 44772
 
6.5%
1544731200 44771
 
6.5%
1543510800 44581
 
6.4%
1543788000 41184
 
5.9%
Other values (13) 194791
28.1%
ValueCountFrequency (%)
1543154400 504
 
0.1%
1543251600 10164
 
1.5%
1543255200 37767
5.4%
1543320000 63173
9.1%
1543420800 14925
 
2.2%
ValueCountFrequency (%)
1545109200 26832
3.9%
1545076800 39312
5.7%
1545022800 5616
 
0.8%
1544990400 41184
5.9%
1544968800 3744
 
0.5%

apparentTemperatureMin
Real number (ℝ)

Distinct137
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.73100157
Minimum11.81
Maximum40.05
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:30:07.982135image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum11.81
5-th percentile13.52
Q127.76
median30.13
Q335.71
95-th percentile39.41
Maximum40.05
Range28.24
Interquartile range (IQR)7.95

Descriptive statistics

Standard deviation7.110493905
Coefficient of variation (CV)0.2391609273
Kurtosis0.8354092094
Mean29.73100157
Median Absolute Deviation (MAD)3.6
Skewness-1.10803535
Sum20605694.99
Variance50.55912357
MonotonicityNot monotonic
2023-06-03T22:30:08.090255image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30.03 20436
 
2.9%
29.97 14976
 
2.2%
29.11 14925
 
2.2%
37.17 14664
 
2.1%
29.88 13259
 
1.9%
32.26 12480
 
1.8%
35.85 11232
 
1.6%
36.46 11232
 
1.6%
39.41 11232
 
1.6%
28.06 11232
 
1.6%
Other values (127) 557403
80.4%
ValueCountFrequency (%)
11.81 1872
 
0.3%
11.82 4368
0.6%
11.83 3744
0.5%
11.86 5616
0.8%
11.99 1872
 
0.3%
ValueCountFrequency (%)
40.05 5460
0.8%
39.9 1872
 
0.3%
39.73 5616
0.8%
39.65 5616
0.8%
39.59 3744
0.5%
Distinct29
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1544048035
Minimum1543136400
Maximum1545134400
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:30:08.203782image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1543136400
5-th percentile1543291200
Q11543399200
median1543744800
Q31544788800
95-th percentile1545044400
Maximum1545134400
Range1998000
Interquartile range (IQR)1389600

Descriptive statistics

Standard deviation687186.1915
Coefficient of variation (CV)0.000445054931
Kurtosis-1.562617462
Mean1544048035
Median Absolute Deviation (MAD)367200
Skewness0.4485043751
Sum1.070134915 × 1015
Variance4.722248618 × 1011
MonotonicityNot monotonic
2023-06-03T22:30:08.312304image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
1543399200 79619
 
11.5%
1543377600 63173
 
9.1%
1543291200 47931
 
6.9%
1544929200 44928
 
6.5%
1545044400 44928
 
6.5%
1543896000 44772
 
6.5%
1544688000 44771
 
6.5%
1543550400 44581
 
6.4%
1545019200 41184
 
5.9%
1543748400 35568
 
5.1%
Other values (19) 201616
29.1%
ValueCountFrequency (%)
1543136400 504
 
0.1%
1543291200 47931
6.9%
1543377600 63173
9.1%
1543392000 14925
 
2.2%
1543399200 79619
11.5%
ValueCountFrequency (%)
1545134400 26832
3.9%
1545044400 44928
6.5%
1545019200 41184
5.9%
1545012000 3744
 
0.5%
1544929200 44928
6.5%

apparentTemperatureMax
Real number (ℝ)

Distinct125
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41.99734255
Minimum28.95
Maximum57.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:30:08.473327image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum28.95
5-th percentile32.68
Q136.57
median40.95
Q344.12
95-th percentile56.37
Maximum57.2
Range28.25
Interquartile range (IQR)7.55

Descriptive statistics

Standard deviation6.936840746
Coefficient of variation (CV)0.1651733258
Kurtosis-0.427701504
Mean41.99734255
Median Absolute Deviation (MAD)4.18
Skewness0.6104055897
Sum29107140.2
Variance48.11975954
MonotonicityNot monotonic
2023-06-03T22:30:08.594870image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.57 20436
 
2.9%
43.84 18408
 
2.7%
43.85 18096
 
2.6%
32.95 14976
 
2.2%
36.58 14976
 
2.2%
35.95 14976
 
2.2%
35.75 14925
 
2.2%
53.8 13104
 
1.9%
53.62 13104
 
1.9%
38.39 13104
 
1.9%
Other values (115) 536966
77.5%
ValueCountFrequency (%)
28.95 901
0.1%
29.83 1674
0.2%
29.98 1716
0.2%
30.25 156
 
< 0.1%
30.27 1858
0.3%
ValueCountFrequency (%)
57.2 11232
1.6%
56.85 5616
0.8%
56.75 5616
0.8%
56.6 7488
1.1%
56.41 3744
 
0.5%
Distinct27
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1544047994
Minimum1543186800
Maximum1545109200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2023-06-03T22:30:08.706381image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1543186800
5-th percentile1543251600
Q11543438800
median1543788000
Q31544817600
95-th percentile1545076800
Maximum1545109200
Range1922400
Interquartile range (IQR)1378800

Descriptive statistics

Standard deviation691077.652
Coefficient of variation (CV)0.0004475752403
Kurtosis-1.571575704
Mean1544047994
Median Absolute Deviation (MAD)468000
Skewness0.4209200773
Sum1.070134887 × 1015
Variance4.775883211 × 1011
MonotonicityNot monotonic
2023-06-03T22:30:08.805897image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
1543438800 66360
 
9.6%
1543320000 63173
 
9.1%
1543690800 44928
 
6.5%
1544817600 44928
 
6.5%
1544896800 44928
 
6.5%
1543852800 44772
 
6.5%
1543510800 44581
 
6.4%
1544986800 41184
 
5.9%
1543788000 41184
 
5.9%
1545076800 39312
 
5.7%
Other values (17) 217721
31.4%
ValueCountFrequency (%)
1543186800 504
 
0.1%
1543244400 22980
 
3.3%
1543251600 24951
 
3.6%
1543320000 63173
9.1%
1543420800 14925
 
2.2%
ValueCountFrequency (%)
1545109200 26832
3.9%
1545080400 5616
 
0.8%
1545076800 39312
5.7%
1544986800 41184
5.9%
1544958000 3744
 
0.5%